Novel Clinically Relevant Genes in Gastrointestinal Stromal Tumors Identified by Exome Sequencing

Published OnlineFirst August 13, 2013; DOI: 10.1158/1078-0432.CCR-12-3863

Clinical Cancer Human Cancer Biology Research

Novel Clinically Relevant Genes in Gastrointestinal Stromal Tumors Identiﬁed by Exome Sequencing

Sebastian F. Schoppmann1, Ursula Vinatzer1, Niko Popitsch5, Martina Mittlbock€ 2, Sandra Liebmann-Reindl1, Gerd Jomrich1, Berthold Streubel3, and Peter Birner4

Abstract Purpose: Chromosomal gains and losses resulting in altered gene dosage are known to be recurrent in gastrointestinal stromal tumors (GIST). The aim of our study was the identiﬁcation of clinical relevant genes in these candidate regions. Material and Methods: A cohort of 174 GIST was investigated using DNA array (n ¼ 29), FISH (n ¼ 125), exome sequencing (n ¼ 13), and immunohistochemistry (n ¼ 145). Results: Array analysis revealed recurrent copy number variations (CNVs) of chromosomal arms 1p, 1q, 3p, 4q, 5q, 7p, 11q, 12p, 13q, 14q, 15q, and 22q. FISH studies of these CNVs showed that relative loss of 1p was associated with shorter disease-free survival (DFS). Analysis of exome sequencing concentrating on target regions showing recurrent CNVs revealed a median number of 3,404 (range 1,641–13,602) variants (SNPs, insertions, deletions) in each tumor minus paired blood sample; variants in at least three samples were observed in 37 genes. After further analysis, target genes were reduced to 10 in addition to KIT and PDGFRA. Immunohistochemical investigation showed that expression of SYNE2 and DIAPH1 was associated with shorter DFS, expression of RAD54L2 with shorter and expression of KIT with longer overall survival. Conclusion: Using a novel approach combining DNA arrays, exome sequencing, and immunohistochemistry, we were able to identify 10 target genes in GIST, of which three showed hithero unknown clinical relevance. Because the identiﬁed target genes SYNE2, MAPK8IP2, and DIAPH1 have been shown to be involved in MAP kinase signaling, our data further indicate the important role of this pathway in GIST. Clin Cancer Res; 19(19); 5329–39. 2013 AACR.

Introduction known to inhibit both KIT and PDGFRA receptors and Gastrointestinal stromal tumors (GIST) are the most used in the treatment of recurrent and metastatic GIST or common mesenchymal tumors of the gastrointestinal tract GIST with high risk of progression (5). Effectiveness of (1). They are thought to arise from Cajal cells or their imatinib mesylate depends on the mutational status of KIT PDGFRA precursors and characteristically harbor gain of function and (3). In contrast to metastatic GIST, mutations in KIT leading to constitutive activation of the radical surgery seems to be the best treatment option for KIT receptor (2). localized tumors (6). The recurrence rate after radical An alternative mutation in a related tyrosine kinase, surgery seems to depend mainly on tumor localization, PDGFRA, is found in 35% of KIT mutation negative GIST size, and mitotic activity and ranges between 5% and (3, 4). Imatinib mesylate is a molecularly targeted drug 75% with a poor clinical outcome in relapsed patients (7, 8). Current classifications take into account tumor size, mitotic rate, and tumor location but do not include Authors' Affiliations: 1Department of Surgery; 2Center for Medical Sta- mutational data nor protein expressions of tumor cells 3 tistics, Informatics, and Intelligent Systems; Department of Obstetrics and (9–11). Gynecology and Core Unit Next Generation Sequencing; 4Clinical Institute of Pathology, Medical University of Vienna; and 5Center for Integrative The discovery of KIT and PDGFRA activating mutations in Bioinformatics Vienna (CIBIV), Max F Perutz Laboratories, University of the majority of GIST represents a significant progress in Vienna & Medical University of Vienna, & Faculty of Computer Science, University of Vienna, Vienna, Austria understanding their biological behavior. Although further molecular mechanisms underlying the development and Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/). progression of GIST are not fully understood, they are nec- essary due to the wide range of clinical behavior. Chromo- Corresponding Author: Berthold Streubel, Department of Obstetrics and Gynecology, Medical University of Vienna, Wahringer€ Gurtel€ 18-20, A-1090 somal gains and losses resulting in altered gene dosage are Vienna, Austria. Phone: 43-1404002821; Fax: 43-1404002862; E-mail: known to be recurrent in GIST and believed to have a role [email protected] in the molecular pathogenesis of these tumors (12–19). doi: 10.1158/1078-0432.CCR-12-3863 Nevertheless, the target genes remain to be identified within 2013 American Association for Cancer Research. these regions.

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Microarray analysis Translational Relevance High-quality genomic DNA was obtained from 29 fresh- Gastrointestinal stromal tumors (GIST) are the most frozen tumor samples using the DNeasy Blood & Tissue Kit common mesenchymal tumors of the gastrointestinal (Qiagen) and subjected to microarray analysis using the tract, characterized by uncertain clinical behavior. In commercially available Affymetrix Genome-Wide Human addition to KIT, there is a strong need for further SNP Array 6.0 (Affymetrix Inc.) following the protocols therapeutic targets in GIST. Using a technical approach provided by the manufacturer. Data analysis was conducted combining DNA array analysis, next generation exome with Affymetrix Genotyping Console 3.0.1 using the Bird- sequencing, and immunohistochemistry, we were able seed Algorithm and Affymetrix Chromosome Analysis Suite to identify 10 novel, frequently mutated genes in GIST, 1.01 at a resolution of 500 kb. Genome annotations applied of which 3 showed hithero unknown clinical rele- in data analysis referred to the human reference assembly vance. Because a part of the identified target genes has GRCh37/hg19 as provided by the Affymetrix annotation file been shown to be involved in MAP kinase signaling, release na31. The reference model file used for data nor- our data further indicate the important role of this malization with GTC was generated from 39 healthy control pathway in GIST. So the inclusion of MAP kinase individuals. CNVs showing an overlap greater than 80% pathway parameters in future clinical studies might with benign CNVs of the Database of Genomic Variants be of potential benefit for patients as selective inhibi- (http://projects.tcag.ca/variation/) were excluded from our tors are available. analysis. Somatic CNV status of matching tumor-blood/normal tissue samples was used to confirm gains and losses using TaqMan real-time PCR or FISH. The aim of our study was the identification of putative prognostic markers within the regions with recurrent FISH analysis gains or losses. We measured copy number variations Tissue microarrays from 125 GIST paraffin-embedded (CNVs) and defined exact chromosomal breakpoints for samples were used for FISH. Screening for CNVs was con- the most common alterations in GIST. CNVs were screened ducted using commercially available probes for TP73 (chro- in a large single-center cohort of GIST and correlated with mosomal band 1p36), ABL2 (1q25), CCND1 (11q13), clinical outcome. Exome sequencing identified mutated DLEU (13q14), IGH (14q32), SNRPN (15q11), and CLTCL1 candidate genes in the regions of interest, and protein (22q11.2; Abbott and Kreatech). FISH procedures and anal- products of identified target genes were investigated immu- yses were conducted according to standard protocols. nohistochemically in our large single-center cohort of GIST. Immunohistochemical analysis Tissue microarrays containing 145 GIST samples were used for evaluation of protein expression. Supplementary Patients and Methods Table S2 summarizes the antibodies used. Patients Immunohistochemical analysis was conducted using a We studied a total of 174 cases of GIST treated at the Benchmark Ultra Immunostainer (Ventana), except for exp- Medical University of Vienna between August 1992 and ression of RB, where a DAKO autostainer (DAKO) was used. February 2011 in this retrospective observational study. A specimen was considered to be positive if the vast majority Clinical data and follow-up were available for 145 of 174 of cells (>80%) showed distinct staining. The number of cases. All cases were restaged according to UICC TNM cases differed between antibodies due to the use of tissue classification of malignant tumors 7th edition and risk microarrays, and for investigation of FLT4 and AP1B1 the was evaluated according to Fletcher and Miettinen (9– blocks had to be recut, resulting in the loss of several spots. 11). As this cohort of patients has been used in several previous studies, clinical data in correlation with known Exome studies risk factors have been reported previously, as well as the Thirteen of the 29 GIST of the microarray study were results of the sequence analysis about mutations of KIT subjected to high-throughput sequencing. In all these cases, (exons 9, 11, 13, and 17) and PDGFRA (exons 12 and 18; matched control DNA obtained from the peripheral blood refs. 20–22). Tissue microarrays were established for or normal gastric tissue of patients were sequenced in immunohistochemical screening in all 145 cases. FISH parallel. Exome enrichment was conducted using the Tru- was conducted on tissue microarrays of paraffin-embed- Seq sample prep (Illumina). Sequencing was conducted on ded tissue in 125 of 145 cases. Apart from the 145 cases a HiSeq 2000 (Illumina). All datasets were aligned with with clinical follow-up data and paraffin-embedded tis- BWA v 0.6.1-r104 against the human g1k v37 genome using sue available, further 29 GIST cases were identified with standard parameters. We conducted INDEL realignment fresh-frozen tumor material suitable for microarray anal- with GATK v1.4, removed PCR duplicates using Picard ysis and next generation sequencing. Tumor purity was at v1.56 and recalibrated per-base quality values using GATK. least 90% in samples used in all 29 cases. Institutional Variants were then called and filtered using 2 independent review board approval was obtained. pipelines based on GATK’s UnifiedGenotyper (here SNPs

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and INDELs were filtered separately) and SAMTOOLS, tion. All patients underwent initial surgical treatment; 25 respectively. The variant sets were then merged and we patients received adjuvant imatinib mesylate. Median selected all variants from the matched normal-tumor pairs observation time was 37 3 (SE) months. Although 7 that were either unique in the tumor sample or changed patients showed advanced stage disease already at time of their predicted genotype from being heterozygous in the diagnosis, and no complete surgical removal of the GIST normal sample to being homozygous in the cancer sample. was possible, 24 patients experienced recurrent disease, and We annotated these candidate variants using SnpEff 2.0.4 12 died. RC1 and predicted the possible effect of a variant (e.g., silent/nonsilent/nonsense mutation) using the NCBI Ref- Recurrent chromosomal gains and losses erence Sequence (RefSeq) gene annotations. We further The microarray technology was conducted to define determined whether a variant was already contained in the recurrent chromosomal regions and to determine exact dbSNP TSI (Toscani in Italia) dataset. Candidate variants breakpoints in 29 GIST tumors. Although the microarray were further annotated using polyphen2 and finally man- platform used allows for the detection of CNVs down to 50 ually filtered and inspected using IGV. Genes were com- kb or smaller, we aimed to assess the minimal region of pared with PubMed, Gene database, and the CancerGenes overlap of recurrent genomic regions that are known to be database for gene selection and priorization. Variants in much larger. Therefore, we used a resolution of 500 kb and candidate genes were confirmed by Sanger sequencing in all found 114 CNVs (43 gains and 71 losses) in the 29 tumor tested cases. samples altogether (median number of CNVs/sample). We compared the CNVs between the 29 cases and defined Statistical analysis rearrangements as recurrent when observed in at least 3 Categorical data were described with absolute and rela- cases. Eighty-five of the 114 CNVs (75%) were located tive frequencies. Corresponding 95% confidence intervals within recurrent rearrangements and included losses of n ¼ n ¼ n ¼ (95% CI) were calculated according to the method of chromosomal arms 1p ( 13), 3p ( 4), 13q ( n ¼ n ¼ n ¼ Wilson. Group differences were tested by x2 test or by Fisher 5), 14q ( 17), 15q ( 7), and 22q ( 11) as well as n ¼ n ¼ n ¼ exact test in the case of sparse data. Continuous data are gains of chromosomal arms 1q ( 3), 4q ( 6), 5q ( n ¼ n ¼ n ¼ described with median, minimum, and maximum. Differ- 8), 7p ( 3), 11q ( 4), and 12p ( 3; Table 2). ences between 2 groups for continuous and ordinal data CNVs were confirmed in all samples by FISH and TaqMan were tested by Mann–Whitney U test. assays (1p: Hs05732825_cn; 3p: Hs01499513_cn; 5q: Disease-free survival (DFS) was defined from the day of Hs02944177_cn; 11q: Hs06329804_cn; 13q:Hs07026395_cn; surgery until first evidence of progression of disease if 14q:Hs02834878_cn; 15q: Hs05354966_cn; 22q: complete surgical resection was possible. Patients showing Hs01356996_cn). advanced disease at time of initial diagnosis were excluded A detailed list of CNVs is provided in Table 2. In conclu- from analysis of DFS. Overall survival (OS) was defined as sion, we found that the majority of chromosomal imbal- the time from primary surgery to patients’ death. Survival ances were recurrent, indicating that candidate genes rele- data were graphically presented by Kaplan–Meier graphs vant for GIST pathogenesis are located in these regions. and/or described by survival at predefined time points. Group differences are tested by the log-rank test. Cox Gains and losses in correlation with clinico-pathologic regression models were used to estimate the effect of the data expression of proteins adjusted for patients’ age (<60 vs. In a next step, we investigated if recurrent CNVs are of 60) and risk according to Fletcher’s score. Group differ- prognostic relevance. Seven of the 12 regions (1p, 1q, 11q, ences are quantified with HR and corresponding 95% CIs. 13q, 14q, 15q, and 22q) were investigated on tissue micro- Proportional hazards assumptions were graphically che- arrays containing 125 GIST tumors. About the remaining 5 cked by log-minus-log plots in stratified Cox regression regions, commercially available probes did not provide models for every variable in the Cox model separately. reliable signals on the tissue microarrays. A two-tailed P-value of 0.05 was considered as signif- Results about frequencies of losses and gains are sum- icant. SPSS 20.0 (IBM) was used for all calculations. For marized in Supplementary Table S1 and were comparable exploratory purposes, all P values together were also adjust- to DNA microarrays. CNV status of investigated regions was ed to result in a false discovery rate (FDR) of 0.05 as correlated with clinical risk factor, tumor localization, DFS, KIT PDGFRA described by Benjamini and Hochberg (23). Significant OS, and and mutations status. results after FDR-adjustment are marked by "a". FISH for chromosome 1p was successful in 119 samples. Loss of 1p (Fig. 1) was seen in 11 samples (9.2%; 95% CI, 5.2–15.8%), in 5 additional cases, a chromosomal imbal- Results ance between 1p and 1q was observed (5 1p/1qþ). When Clinical characteristics of patients investigating the 16 cases (13.4%; 95% CI, 8.5–20.7%) with Table 1 summarizes the clinical data of the 145 patients relative imbalance of 1p against all other cases, no associ- with available clinical and follow up data. In brief, 94 GIST ation with clinical risk factor was seen either, but these cases (64.8%) were of gastric localization (64.8%), 92 (63.4%) showed a significantly shorter DFS (5 years DFS rate: 40.4% showed a KIT mutation, and 21 (14.5%) a PDGFRA muta- 17% SE vs. 84.6% 4.4% SE, P ¼ 0.012, log-rank test) but

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Table 1. Clinico-pathologic data of 145 GIST patients included into this study

Number of 5 Years disease-free 5 years overall Factor cases survival rate SE survival rate SE Localization P < 0.001a P > 0.05 Gastric 94 (64.8%) 89.8 4.3% – Duodenum 6 (4.1%) 100% – Small intestine 27 (18.6%) 62.2 10.1% – Rectum 3 (2.1%) 100% – Other 15 (10.3%) 45.1 14.9% – Risk Fletcher P ¼ 0.001a P < 0.001a Very low 16 (11%) 87.5 11.7% 100% Low 50 (34.5%) 93.9 4.2% 95.5 4.4% Intermediate 32 (22.1%) 79 8.6% 96.4 3.5% High 47 (32.4%) 54.8 9.7% 73.8 7.8% Risk Miettinen P < 0.001a P < 0.001a None 18 (12.4%) 90 9.5% 100% Very low 38 (26.2%) 96.3 3.6% 93.8 6.1% Low 28 (19.3%) 77 10.7% 95.8 4.1% Moderate 17 (11.7%) 84.6 10% 100% High 29 (20%) 59.9 12.4% 65.5 9.7% Insufﬁcient data 15 (10.3%) 45.1 14.9% 83.3 15.2% Staging UICC P < 0.00a P > 0.05 pT1 19 (13.1%) 90 9.5% – pT2 65 (44.8%) 84.5 6.2% – pT3 40 (27.6%) 73.6 8.9% – pT4 21 (14.5%) 50.5 12.9% – Mitotic rate UICC P ¼ 0.001a P < 0.001a Low 96 (66.2%) 87.1 4.5% 96.7 2.4% High 49 (33.8%) 58.9 8.9% 75.8 7.1% Synchronous metastases P ¼ 0.003a P < 0.001a No 131 (90.3%) 80.7 4.3% 94.6 2.7% Yes 14 (9.7%) 47.3 19% 51.3 12.5% KIT mutation P > 0.05 P > 0.05 No 53 (36.6%) –– Yes 92 (63.4%) –– PDGFRA mutation P > 0.05 P > 0.05 No 124 (85.5%) –– Yes 21 (14.5%) ––

aSigniﬁcant results after FDR adjustment.

not OS (Fig. 2). A significant association of relative loss of 1p of 18 (44.4%: 95% CI, 24.6–66.3%) small intestinal GIST]. with localization of the GIST was found (P ¼ 0.001a, x2 Deletion of 22q correlated with the presence of KIT muta- test). So of 75 gastric GIST, only 4 (5.3%; 95% CI, 5.2– tions. Although in GIST without KIT mutation (n ¼ 28), 33.4%) showed relative loss of 1p, but 9 of 28 (32.1%; 95% only 3 cases (10.7%; 95% CI, 3.7–27.2%) showed a 22q CI, 17.9–50.7%) of small intestinal GIST. deletion, there were 15 of 47 (32%; 95% CI, 20.4–46.2%) FISH for 15q was successful in only 73 samples, and a GIST with KIT mutation (P ¼ 0.038, x2 test). significant association of 15q deletion with tumor localization was seen (P < 0.001a, Fisher exact test), because only Candidate genes within gains and losses 2 of 46 gastric (4.4%; 95% CI, 1.2–14.5%) GIST showed In a next step, we compared the recurrent CNVs that were 15q deletion, but 8 of 17 (47.1%; 95% CI, 26.2–69%) small observed in at least 3 cases (i.e., >10% of total cases) and intestinal GIST. defined minimal regions of overlap shared by all aberrant FISH for 22q was successful in only 75 GIST, and 22q cases. The results are listed in Table 2. The size of the deletion correlated with gastric localization [P ¼ 0.01, x2 minimal regions of interest and consecutively the number test; 7 of 48 (14.6%: 95% CI, 7.3–27.2%) gastric GIST, vs. 8 of genes were too large to identify relevant candidates for the

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Table 2. Copy number variations assessed by DNA array (n ¼ 29)

Chromosome arm Type of CNV Cases (n/%; 95% CI) ROI Start bp ROI End bp Size (Mb) 1p Loss 13 (45%; 95% CI, 28–63%) 5657217 16851502 11.2 3p Loss 4 (19%; 95% CI, 6–31%) 47478496 50156251 2.7 13q Loss 5 (17%; 95% CI, 8–35%) 45307552 49798504 4.5b 14q Lossa 17 (59%; 95% CI, 41–75%) 26370859 28652135 2.3 41327139 46436189 5.1 54142190 106897379 52.8 15q Loss 7 (24%; 95% CI, 12–42%) 49340635 56142902 6.8 22q Loss 11 (38%; 95% CI, 23–56%) 28772816 51134186 22.4 1q Gain 3 (10%; 95% CI, 5–33%) 118649839 249224376 232.4 4q Gain 6 (21%; 95% CI, 10–38%) 52920476 56180478 3.3c 5q Gain 8 (28%; 95% CI, 15–46%) 120645755 180645101 60.0 7p Gain 3 (10%; 95% CI, 5–33%) 7058423 62706404 55.7 11q Gain 4 (19%; 95% CI, 6–31%) 78846125 134944770 56.1 12p Gain 3 (10%; 95% CI, 5–33%) 479074 15635796 15.2

ROI (region of interest) denotes minimal region of overlap, genome annotations applied in data analysis refer to the human reference assembly GRCh37/hg19. aThe minimal region of overlap on chromosome 14 comprised 3 regions with a total size of 60.2 Mb. bRB1 is located within the minimal region of overlap. cKIT and PDGFRA are located within the minimal region of overlap, respectively. majority. Interestingly, the most frequent gain comprised a 37 genes with the Cancer Genes Database, the Gene Data- small region on chromosome 4 that included KIT and base, and GIST publications. Results are listed in Table 3. PDGFRA. Furthermore, RB1, which was recently reported This strategy reduced the number of candidate genes to 3 or to be a strong predictor of clinical outcome in GIST, was less per region. As expected KIT, PDGFRA, and RB1 were located in the deleted small region of overlap on chromo- among these cases. In addition, we searched for potential some 13. We concluded that our strategy identified success- interactions between the 37 genes and found positive fully the 2 most prominent genes in GIST, that is KIT and matches between DIAPH1 and AP1B as well as MAPK8IP2 PDGFRA, within our regions of interest. Nevertheless, the and SYNE2. candidate remained elusive for the other regions. Protein expression in correlation with risk factors Exome sequencing for the identification of novel Eleven candidate genes were selected for immunohisto- candidate genes chemical evaluation (Table 4 and Supplementary Table Exome sequencing was conducted to identify putative S2). Table 4 shows the number of GIST samples investigat- novel candidate genes within the defined regions of interest ed, the primary staining pattern, and the number of positive as outlined in Table 2. We compared tumors with the cases for each antibody. Figure 1 gives samples of immu- matched constitutional genomes of 13 patients. The medi- nostaining. Gene mutation status has been shown to be an overall number of variants/exome was 50,625 (range linked to protein expression in a variety of human genes, but 38,365–58,258) per exome (Supplementary Table S3), the because protein overexpression might indicate loss of func- median number of variants (SNPs, insertions, deletions) tion (e.g., P53; ref. 24) as well as gain of function (KIT, ALK; present in tumor minus paired blood sample was 3,404 refs. 25, 26), protein expression was scored as positive (range 1,641–13,602; Supplementary Table S4). Intergenic versus negative without any hypothesis about the type of and intronic variants were excluded and annotation by altered gene function. snpEff reduced the average number from 3,404 to 1,764 Expression of RBM5, RB, UBPY/USP8, GTSE1, MAPK8IP2, (range 1,012–7,300). These variants included the switch of APIB1, and FLT4 was not associated with risk according to heterozygous mutations to homozygous mutations. Var- Fletcher, Miettinnen, or UICC staging and grading, DFS or iants were considered only when they were stop mutations, OS or metastases at time of diagnosis (Table 4). RAD54L2 splice site mutations, frame shift mutations, or missense expression was associated with higher risk according to mutations with potential pathogenic at in silico prediction. Fletcher (median high vs. intermediate risk; P ¼ 0.033; In a next step we looked for genes with recurrent variants in Mann–Whitney U test) and higher UICC staging (median at least 3 patients. Recurrent variants were found in 37 genes pT3 vs. pT2; P ¼ 0.032; Mann–Whitney U test). Expression of and listed in Table 3. Sanger sequencing confirmed the RAD45L2 was associated with shorter OS (5 years OS rate: variants in all tested cases. Furthermore, we compared the 80.8% 12.2% SE vs. 93.7% 3.2% SE, P ¼ 0.042, log-rank

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2.4% SE vs. 67.2% 16.5% SE, P ¼ 0.011, log-rank test; Fig. 2), but not DFS. The presence of a KIT mutation had no influence on DFS or OS (P > 0.05, log-rank test). A strong correlation of DIAPH1 expression with risk according to Fletcher (median intermediate vs. low risk, P < 0.001a, Mann–Whitney U test), Miettinen (median moderate vs. very low, P < 0.001a, Mann–Whitney U test), and UICC staging (median pT3 vs. pT2, P < 0.001a, Mann–Whitney U test) was seen. In addition, strong DIAPH1 expression was associated with high mitotic rate according to UICC (45.1% vs. 15.6%, P ¼ 0.001a, x2 test) and small intestinal localization (17 of 30 vs. 26 of 74 in gastric GIST; P ¼ 0.043, c2 test). Expression of DIAPH1 was associated with shorter DFS (5 years DFS rate: 57.3% 10.2% SE vs. 92.8% 4.1% SE months, P ¼ 0.007, log-rank test; Fig. 2), but not with shorter OS (P > 0.05, log-rank test). In a Cox regression model adjusting for patients’ age and Fletchers score, SYNE2 expression was still associated with shorter DFS (P ¼ 0.046; HR ¼ 2.85; 95% CI, 1.02–7.97), and expression of DIAPH1 with longer OS (P ¼ 0.030; HR ¼ 0.16; 95% CI, 0.03–0.84). When also including synchronous metastases, adjuvant administration of imatinib mesylate, KIT and PDGFRA mutations into the regression models, SYNE2 expression remained an independent prognostic factor for shorter DFS (P ¼ 0.012; HR ¼ 3.92; 95% CI, 1.35–11.42), whereas no relevance of KIT and PDGFRA mutations or adjuvant imatinib mesylate administration was observed. A prognostic relevance of DIAPH1 expression on OS (P ¼ 0.042; HR ¼ 0.16; 95% CI, 0.03–0.95) was seen after KIT PDGFRA Figure 1. Samples of FISH and immunostaining. A, GIST with loss of 1p at introduction of and mutations into the regres- FISH. Original magnification 1,000. B, GIST positive for KIT. Original sion model, but this was not evident any more (P ¼ 0.077) magnification 100. C, GIST positive for RAD54L2. Original after inclusion of imatinib mesylate administration and fi magni cation 400. D, GIST negative for RAD54L2. Original synchronous metastases. KIT and PDGFR mutations showed magnification 400. E, GIST positive for SYNE2. Original magnification 400. F, GIST negative for SYNE2. Original magnification 400. G, GIST again no prognostic relevance. positive for DIAPH1. Original magnification 400. H, GIST negative for No significant additional effect of RAD54L2 or Kit expres- DIAPH1. Original magnification 400. sion was seen to explain DFS and OS additional to the effect of patients’ age and Fletcher score (P > 0.05). test; Fig. 2), but not with shorter DFS. High SYNE2 expres- A combination of combined SYNE2 and DAPH1 expression was associated with high mitotic rate according to UICC sion showed a prognostic relevance for DFS in univariate (60% vs. 26.9%; P < 0.001a, x2 test) and with higher risk analysis (5 years DFS rate: 25% 19.4% SE vs. 85.7% according to Fletcher and Miettinnen (P ¼ 0.044 and 0.031, 4.4% SE, P ¼ 0.001a, log-rank test; Fig. 2) as well as after respectively; Mann–Whitney U tests) and shorter DFS (5 adjustment for patients’ age and Fletchers score in a mul- years DFS rate: 43.1% 14.1% SE vs. 87.2% 4.2% SE, P ¼ tivariate Cox regression (P ¼ 0.025; HR ¼ 3.58; 95% CI, 0.001a, log-rank test) but not OS (P ¼ 0.06, log-rank 1.17–10.90). The prognostic relevance was also seen (P ¼ test; Fig. 2). In addition, SYNE2 expression was less common 0.01; HR ¼ 4.94; 95% CI, 1.17–16.55) when introducing in gastric (7 of 80) than in small intestinal GIST (9 of 22; P ¼ adjuvant imatinib mesylate, synchronous metastases, KIT 0.006a, x2 test). and PDGFRA mutations (in addition to age and Fletcher A correlation of SYNE2 and MAPK8IP2 protein expression score) into the regression model. was seen (P ¼ 0.014; x2 test), but not between DIAPH1 and The combination of SYNE2 and RAD54L2 expression, AP1B1 due to the overexpression of the latter in all samples. which was only evident in 2 patients, was associated with GTSE1 expression was more common in small intestinal shorter OS in univariate analysis (P < 0.001a, log-rank test), (7 of 22) than gastric (5 of 69) GIST (P ¼ 0.013, x2 test). but did not reach significance in multivariate analysis of OS. Kit expression correlated with lower risk according to The combination of expression of target genes with high Fletcher (median intermediate vs. high risk, P ¼ 0.035, UICC mitotic rate delivered no additional prognostic infor- Mann–Whitney U test), and lower UICC staging (median mation (P > 0.05, Cox regression). pT2 vs. pT3; P ¼ 0.007, Mann–Whitney U test). Expression No protein was associated with the presence of metastases of Kit was associated with longer OS (5 years OS rate: 94.5% already at time of surgery (P > 0.05, c2 test). Kit protein

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A B 1,0 1,0 RAD54L2–

0,8 No relative loss 1p36 0,8 RAD54L2+

0,6 0,6

0,4 0,4

0,2 Relative loss 1p36 0,2 Cumulative overall survival overall Cumulative Cumulative disease-free survival Cumulative P P 0,0 = 0.012, log-rank test 0,0 = 0.042, log-rank test

,00 1000,00 2000,00 3000,00 4000,00 5000,00 6000,00 ,00 1000,00 2000,00 3000,00 4000,00 5000,00 6000,00 Time since surgery (days) Time since surgery (days) C D 1,0 1,0

Kit+ 0,8 SYNE2– 0,8

Kit– 0,6 0,6

0,4 SYNE2+ 0,4

0,2 0,2 Cumulative overall survival overall Cumulative Cumulative disease-free survival Cumulative P = 0.001, log-rank test P = 0.011, log-rank test 0,0 0,0

,00 1000,00 2000,00 3000,00 4000,00 5000,00 6000,00 ,00 1000,00 2000,00 3000,00 4000,00 5000,00 6000,00 Time since surgery (days) Time since surgery (days) E F 1,0 1,0

DIAPH1– 0,8 0,8 SYNE2/DIAPH1–

0,6 0,6 DIAPH1+

0,4 0,4

SYNE2/DIAPH1+ 0,2 0,2 Cumulative disease-free survival Cumulative disease-free survival Cumulative P P 0,0 = 0.007, log-rank test 0,0 = 0.001, log-rank test

,00 1000,00 2000,00 3000,00 4000,00 5000,00 6000,00 ,00 1000,00 2000,00 3000,00 4000,00 5000,00 6000,00 Time since surgery (days) Time since surgery (days)

Figure 2. Kaplan–Meier curves of DFS and OS, ticks indicate censored observations. A, DFS according to relative loss of 1p. B, OS according to RAD45L2 expression. C, DFS according to SYNE2 expression. D, OS according to Kit expression. E, DFS according to DIAPH1 expression. F, DFS according to a combination of SYNE2 and DIAPH1 expression (SYNE2/DIAPH1þ) versus all other cases (SYNE2/DIAPH1).

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Table 3. Results of exome sequencing in 13 patients

Potential Type Number Potentially PubMed oncogenic Region deﬁned of genes Genes with oncogenic Search: according of by with recurrent (according to Gene AND to Gene interest microarray variants variations Number of cases (95% CI) Cancer genes) GIST Database 1p Loss 48 GPR153 4 (31%; 95% CI, 13–58%) No No No LOC440563 4 (31%; 95% CI, 13–58%) No No No PRAMEF19 4 (31%; 95% CI, 13–58%) No No No CROCC 5 (39%; 95% CI, 18–65%) No No Yes PRAMEF1 6 (46%; 95% CI, 23–71%) No No Yes HNRNPCL1 7 (54%; 95% CI, 29–77%) No No Yes 3p Loss 33 ALS2CL 3 (23%; 95% CI, 8–50%) No No Yes COL7A1 3 (23%; 95% CI, 8–50%) No No No LAMB2 3 (23%; 95% CI, 8–50%) No No Yes MST1 3 (23%; 95% CI, 8–50%) No No Yes RBM5a 3 (23%; 95% CI, 8–50%) Yes No Yes RAD54L2a 4 (31%; 95% CI, 13–58%) Yes No Yes 13q Loss 9 FAM194B 4 (31%; 95% CI, 13–58%) No No Yes RB1a 3 (23%; 95% CI, 8–50%) Yes Yes Yes 14q Loss 64 SYNE2a,b 3 (23%; 95% CI, 8–50%) No No Yes GALC 3 (23%; 95% CI, 8–50%) No No No DYNC1H1 5 (39%; 95% CI, 18–65%) No No No AHNAK2 6 (46%; 95% CI, 23–71%) No No No 15q Loss 12 MYO5A 3 (23%; 95% CI, 8–50%) No No No USP8a 5 (39%; 95% CI, 18–65%) No No Yes 22q Loss 80 AP1B1c 3 (23%; 95% CI, 8–50%) No No Yes NEFH 3 (23%; 95% CI, 8–50%) No No No SEC14L4 3 (23%; 95% CI, 8–50%) No No No RFPL3 3 (23%; 95% CI, 8–50%) No No No GTSE1a 3 (23%; 95% CI, 8–50%) Yes No Yes MAPK8IP2a,b 3 (23%; 95% CI, 8–50%) Yes No Yes TUBGCP6 4 (31%; 95% CI, 13–58%) No No No 4q Gain 4 PDGFRA 3 (23%; 95% CI, 8–50%) Yes Yes Yes KITa 6 (46%; 95% CI, 23–71%) Yes Yes Yes 5q Gain 100 DIAPH1a,c 3 (23%; 95% CI, 8–50%) Yes No Yes FAT2 3 (23%; 95% CI, 8–50%) Yes No Yes PCDHB8 3 (23%; 95% CI, 8–50%) No No No TCOF1 3 (23%; 95% CI, 8–50%) No No No YIPF5 3 (23%; 95% CI, 8–50%) No No No C5orf65 4 (31%; 95% CI, 13–58%) No No No CDHR2 4 (31%; 95% CI, 13–58%) No No Yes F12 4 (31%; 95% CI, 13–58%) No No No FLT4a 4 (31%; 95% CI, 13–58%) Yes Yes Yes

aProtein expressions were evaluated immunohistochemically and correlated with risk factors. bPotential interaction. cPotential interaction.

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expression was found significantly more often in mutated tumors (P < 0.001a, c2 test; 93.5% vs. 74.1%), whereas expression of all other proteins showed no association with KIT PDGFRA – KIT mutations – or mutation. A correlation of RB 1 expression with loss at 13q was seen (P ¼ 0.017, Fisher exact test), whereas in GIST without nuclear RB1 expression, 24 of 66 (36.4%) showed a deletion on 13q, there were only 1 of 17 (5.9%) in patients positive for RB1 expression. In summary, expression of RAD54L2, SYNE2, KIT, and DIAPH1 corre- Shorter OS –– Longer OSShorter DFS Yes lated with risk factors and survival. In rearward stepwise Cox regression models of DFS and OS including all relevant parameters, SYNE2 expression (P ¼ 0–018; HR ¼ 3.8; 95% CI, 1.26–11.48) remained an independent prognostic factor for DFS and DIAPH1 expression for OS (P ¼ 0.042; HR ¼ 0.59; 95% CI, 0.004–0.9) in Small intestinal – – the last step of the regression models, respectively (Supple- mentary Table S5). Discussion Yes Small intestinal Shorter DFS UICC mitotic rate Localization–– Survival In this study, we combined several techniques to identify putative prognostic factors within genomic GIST target regions. Microarray analysis was used to define minimum regions of interest for 12 recurrent gains or losses, FISH Yes (neg.) – Yes UICC staging showed prognostic significance of 1p loss. Exome sequencing identified 37 recurrent potential pathogenic variations, and 11 candidates were chosen for immunhistochemical screening and correlation with clinical data. An association – – Miettinen risk with survival was found for RAD54L2, SYNE2, KIT, and DIAPH1 expressions. KIT is a well-known proto-oncogene in human tumors. Although KIT mutations are a common event in GIST, ––––– –––––– – ––––– – ––––– – – ––––– – – ––––– – – ––––– – – Fletcher risk overexpression of KIT is observed considerably more often, showing no clear association with mutation status (27, 28). Generally, overexpression of KIT serves as primary bio- marker for induction of imitinib therapy (29), whereas the 94.2% 100% 18.8% 58.6% 91.5%54.3% Yes (neg.) 51.3% Yes Yes Yes Yes 95.3% 16.5%27.4% Yes 25.5% Yes Yes – – – – – – – – – – – exact mutation status serves only for adjustment of it (30). The general presence of KIT mutations does not seem to be associated with worse prognosis in GIST, but deletion of exon 11 is accompanied with shorter survival in untreated patients (31). In contrast, other authors found no prognostic relevance of KIT mutations after curative surgical resection of GIST (32). Consensus exists that in patients treated Positive cases 95% CI with imatinib mesylate, KIT exon 9 mutations or lack of KIT mutations are associated with inferior response to imatinib (3, 33). Although many data on immunohistochemical expression of KIT as diagnostic and predictive marker for Cytoplasm 126 (86.9%)Cytoplasm 80.4 30 (40%) 29.7 Nucleus 20 (18.9%) 12.6 Primary staining pattern CytoplasmCytoplasm 108 (90%)Cytoplasm 74 (100%)Cytoplasm 83.3 14 (11.8%) 95.1 69 (50.4%)Cytoplasm 7.1 42.1 54 (45.4%) 36.7 Nucleus 108 (91.5%)Nucleus 85.1 23 (18%) 12.3 Nucleus 11 (9.6%) 5.5 GIST do exist (34), surprisingly few data on the prognostic relevance of KIT expression are available: thus, it was not an independent prognostic factor in 95 GIST (32). In our study, KIT protein expression was found significantly more often in cases with KIT mutation. Lack of KIT expression was associated with shorter OS, but because 6 of 19 IHC-neg- Number of investigated cases ative GIST showed a KIT mutation and 5 of 19 a PDGFRA Expression of proteins and correlation of overexpression with prognostic parameters mutation at sequencing, and 3 patients received imatinib, this subject deserves further investigation in a more homog- enous collective. USP8AP1B1GTSE1 120 MAPK8IP2 74 KIT 137 119 DIAPH1FLT4 119 Abbreviation: 145 neg., negative correlation. 75 RBM5RAD54L2RB1 114 118 SYNE2 106 128 Table 4. Protein Chromosomal gains and losses are consistent findings in GIST. Our data are consistent with previous reports with

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losses of 1p, 3p, 13q, 14q, 15q, and 22q and gains of sion (40). To our knowledge, no DIAPH1 mutations in chromosomes 4 and 5 (12–19). Only one previous study human malignant disease have been described previously. of 25 GIST tumors used the same platform and provided Interestingly, SYNE2 encodes for a nuclear outer mem- comparable high-resolution copy number analysis (17). brane protein and has been shown to play a role in MAP Regions of interest were investigated for candidate genes kinase signaling pathways (MAPK1 and MAPK2) in pro- by gene expression analyses in that study. This approach myelocytic leukemia protein (41). SYNE2 also interacts failed to identify PDGFRA and KIT on chromosome 4 and with MAPK8IP2, which is one of our candidate genes on RB1 on chromosome 13 in contrast to our study using a chromosomes 22 (42), and a correlation of expression of combination with exome sequencing. About the prognostic these 2 proteins was also seen in our study. Interestingly, we relevance of CNVs in GIST, loss of 1p and 15q were reported found recently that high MAPKAPK2 expression is also a to be more common in clinically more aggressive GIST (35). strong prognostic predictor in the GIST cohort investigated Loss of 1p has also been shown to be more common in in this study (21). Because DIAPH1 inhibition has also been intestinal GIST, and was associated with a more aggressive shown recently to block ERK phosphorylation (43), our clinical course in that study as well (36). In contrast, the findings indicate that altered MAP kinase signaling seems to pathway characterized by loss of 14q has been suggested to be of crucial importance in GIST. be associated with gastric tumors with stable karyotypes and In summary, using high-throughput methods we identi- a more favorable clinical outcome (36). In our study, fied several new candidate genes that may be of pathogenetic relative loss of 1p at FISH was significantly associated with and prognostic significance in GIST. Our data indicate that GIST of the small bowel and with more aggressive clinical the MAP kinase signaling pathway seems to play an impor- course, which is in good correlation to previous data tant role in GIST. So the inclusion of MAP kinase pathway obtained by comparative genomic hybridization (36). In parameters in future clinical studies might be of potential contrast to the findings by Gunawan and colleagues, no benefit for the patients as selective inhibitors are available. association of 14q deletion with gastric localization or fl better prognosis was seen in our study (36). Furthermore, Disclosure of Potential Con icts of Interest No potential conflicts of interest were disclosed. we failed to identify loss of RB1 expression as a prognos- tically relevant factor. This is in contrast to recent data, Authors' Contributions where RB1 was integrated in a genomic index for mitotic Conception and design: S.F. Schoppmann, B. Streubel, P. Birner checkpoints that was reported as a strong predictor of Development of methodology: S.F. Schoppmann, P. Birner Acquisition of data (provided animals, acquired and managed patients, clinical outcome in GIST (19). provided facilities, etc.): S.F. Schoppmann, U. Vinatzer, S. Liebmann- Apart from established candidates for 4q gain (KIT and Reindl, G. Jomrich, P. Birner PDGFRA RB1 Analysis and interpretation of data (e.g., statistical analysis, biosta- ) and 13q loss ( ), we were able to provide new tistics, computational analysis): U. Vinatzer, N. Popitsch, M. Mittlbock,€ B. candidates in further recurrent regions of interest, and to Streubel, P. Birner define target genes in previously known areas of CNVs. Writing, review, and/or revision of the manuscript: S.F. Schoppmann, N. RAD54L2 DIAPH1 Popitsch, B. Streubel, P. Birner on chromosomal arm 3p, on 5q and Administrative, technical, or material support (i.e., reporting or orga- SYNE2 on 14q may be of biological relevance because nizing data, constructing databases): G. Jomrich, B. Streubel associations with staging and survival were observed. Study supervision: S.F. Schoppmann, P. Birner Although all 3 genes have not been reported in GIST so Acknowledgments far, no data at all on RAD54L2 in human malignant disease The authors thank Amy Bruno-Lindner for language editing. exist, and there is only one study about SYNE2, where the presence of splice variants was reported in human non– The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked small lung cancer (37). DIAPH1 is a downstream effector of advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate RhoA, controls actin-dependent processes such as cytoki- this fact. nesis, SRF transcriptional activity, and cell motility (38, 39), Received December 19, 2012; revised August 1, 2013; accepted August 1, and might therefore play a role in human cancer progres- 2013; published OnlineFirst August 13, 2013.

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Clin Cancer Res 2013;19:5329-5339. Published OnlineFirst August 13, 2013.

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